- Location
- Gurugram 8 B, India
- Type
- Full-time
- Department
- Engineering
- Seniority
- Entry
- Experience
- 3+ years
- Education
- Master
- Clearance
- Required
- Closing date
- Today
- Source
- Workday
Description
Line of Service
AdvisoryIndustry/Sector
Not ApplicableSpecialism
Data, Analytics & AIManagement Level
AssociateJob Description & Summary
At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.
Job Description & Summary:
We are looking for an experienced AWS Data Engineer with strong expertise in SQL, Python, and PySpark to design, build, and optimize scalable data ingestion and ETL/ELT pipelines. The role requires hands-on experience with AWS services such as Glue, Step Functions, Lambda, and DMS, along with a strong understanding of data engineering best practices, production readiness, and high-volume data processing.
Responsibilities:
Develop ETL/ELT pipelines using AWS services such as Glue, Step Functions, Lambda, and DMS.
Implement direct-to-Aurora ingestion strategies for snapshots and delta loads.
Ensure referential integrity, correct processing order, idempotency, and recovery mechanisms.
Build monitoring, validation, and reconciliation frameworks for production data pipelines.
Manage scalability and throughput during high-volume EOD ingestion workloads.
Mandatory skill sets:
Expert-level SQL development and performance optimization.
Strong proficiency in SQL, Python, and PySpark.
Hands-on experience with ETL pipelines and orchestration frameworks.
Solid understanding of ACID-compliant data ingestion principles.
Experience with schema evolution and CDC (Change Data Capture) patterns.
Experience owning production readiness and end-to-end solution delivery.
Exposure to cloud-native architectures and AWS tools such as Glue, Step Functions, Lambda, and DMS.
Preferred skill sets:
Experience with SAP ODP or enterprise data replication technologies.
Familiarity with distributed PostgreSQL systems.
Exposure to event-driven architectures such as Kafka.
Years of experience required:
Experience: 5–8 years
Minimum 3 years of relevant work experience, typically reflecting 5+ years in data engineering, data integration, or related roles.
Proven track record of building resilient and idempotent ingestion frameworks.
Experience supporting high-volume, time-sensitive processing, especially EOD workloads.
Strong operational mindset, including monitoring, alerting, and maintaining runbooks.
Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Bachelor of Engineering, Master of EngineeringDegrees/Field of Study preferred:Certifications (if blank, certifications not specified)
Required Skills
AWS Database Migration Service (DMS), Database ModelingOptional Skills
Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Data Anonymization, Data Architecture Development, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline, Data Quality, Data Strategy {+ 22 more}Desired Languages (If blank, desired languages not specified)
Travel Requirements
Available for Work Visa Sponsorship?
Government Clearance Required?
Job Posting End Date
May 18, 2026